Traffic scene awareness for intelligent vehicles using ConvNets and stereo vision
Articles
Overview
published in
- ROBOTICS AND AUTONOMOUS SYSTEMS Journal
publication date
- February 2019
start page
- 109
end page
- 122
volume
- 112
Digital Object Identifier (DOI)
full text
International Standard Serial Number (ISSN)
- 0921-8890
Electronic International Standard Serial Number (EISSN)
- 1872-793X
abstract
- In this paper, we propose an efficient approach to perform recognition and 3D localization of dynamic objects on images from a stereo camera, with the goal of gaining insight into traffic scenes in urban and road environments. We rely on a deep learning framework able to simultaneously identify a broad range of entities, such as vehicles, pedestrians or cyclists, with a frame rate compatible with the strict requirements of onboard automotive applications. Stereo information is later introduced to enrich the knowledge about the objects with geometrical information. The results demonstrate the capabilities of the perception system for a wide variety of situations, thus providing valuable information for a higher-level understanding of the traffic situation.
Classification
subjects
- Mechanical Engineering
keywords
- object detection; pose estimation; deep learning; intelligent vehicles